Prostate cancer is a disease with a unique combination of high incidence but low virulence, and therefore represents a major public health challenge in the United States. Population-based screening with a single Prostate Specific Antigen (PSA) test detects mostly low-risk indolent cancers. Diagnosing and treating such low-risk prostate cancer is likely to cause more harm than benefit. The challenge is to improve screening sensitivity and specificity for clinically significant, high-risk prostate cancer so as to be able to preferentially detect cancers that may be clinically lethal; this is an unmet need that is likely to impact quality of life and longevity.
In an attempt to improve PSA-based screening for prostate cancer, researchers have introduced concepts that use multiple serial measures of PSA over time. These concepts are varyingly described as PSA kinetics, PSA growth, PSA rate or PSA velocity (PSAV). Models for determining prostate PSA level change over time have used different assumptions, different statistical methods, and different computational methods. For instance, initial proposals included a multi-phase non-linear model for PSAV computation. Currently, PSAV is derived from linear regression methods or is commonly calculated as the simple average difference of multiple PSA measures.
The totality of the evidence has suggested that known methods for determining PSA kinetics/velocity do not improve prostate cancer detection. Even so, research has shown that on average, the pattern (not just the simple “rate”) of PSA increase is quantitatively and qualitatively different in patients with aggressive prostate cancer as compared to men with localized prostate cancer, other prostate disorders (e.g., benign prostatic hyperplasia, prostatitis), and in those men with no known prostate condition.
Studies have reported different PSA change rate with time for cancer patients, probably because each study used a different cohort of men originally selected for a different research question. In addition, studies have not controlled for important confounders. For example, body mass index (BMI, a measure of relative weight that is derived by dividing the individual's weight, in kilograms (kg), by his height, in meters (m) squared, that is used as a proxy for overweight/obesity), race, and prostate volume have not always included in the models. Another limitation to previous studies is the small number of subjects for most of the included studies.
Multiple definitions for PSAV, lack of a single threshold cut-off value for PSAV, and sensitivity of PSA to biological and bio-behavioral characteristics, such as BMI, race, age, medications and smoking has led to confusion and debate as to whether determination of PSAV improves prostate cancer detection. Some evidence supports its use and some argues against it. Nevertheless, there is general consensus that when measured rigorously, PSA change over time differs quantitatively and qualitatively across men who develop prostate cancer versus those who with benign prostatic hyperplasia (BPH) or normal prostates of apparently healthy men. Even among men with prostate cancer, PSA change over time appears to be different for aggressive prostate cancer patients compared to non-aggressive cancer.
What is needed in the art is a method for determining and utilizing the PSA rate of change to detect aggressive prostate cancer and differentiate from other conditions that are less lethal but may be associated with an elevated PSA measure. It would be of great public health and medical benefit if there were a method for detecting aggressive prostate cancer in asymptomatic men that can be utilized to determine whether or not cancer treatment and/or more invasive diagnostic procedures, such as biopsy, should be carried out.